Computational Models for Trapping Ebola Virus Using Engineered Bacteria

Daniel Perez Martins, Michael Barros, Massimiliano Pierobon, Meenakshisundaram Kandhavelu, Pietro Lio, Sasitharan Balasubramaniam

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

The outbreak of the Ebola virus in recent years has resulted in numerous research initiatives to seek new solutions to contain the virus. A number of approaches that have been investigated include new vaccines to boost the immune system. An alternative post-exposure treatment is presented in this paper. The proposed approach for clearing the Ebola virus can be developed through a microfluidic attenuator, which contains the engineered bacteria that traps Ebola flowing through the blood onto its membrane. The paper presents the analysis of the chemical binding force between the virus and a genetically engineered bacterium considering the opposing forces acting on the attachment point, including hydrodynamic tension and drag force. To test the efficacy of the technique, simulations of bacterial motility within a confined area to trap the virus were performed. More than 60 percent of the displaced virus could be collected within 15 minutes. While the proposed approach currently focuses on in vitro environments for trapping the virus, the system can be further developed into a future treatment system whereby blood can be cycled out of the body into a microfluidic device that contains the engineered bacteria to trap viruses.

Original languageEnglish (US)
Article number8359015
Pages (from-to)2017-2027
Number of pages11
JournalIEEE/ACM Transactions on Computational Biology and Bioinformatics
Volume15
Issue number6
DOIs
StatePublished - Nov 1 2018

Fingerprint

Ebolavirus
Trapping
Viruses
Bacteria
Computational Model
Virus
Trap
Lab-On-A-Chip Devices
Microfluidics
Blood
Hydrodynamics
Motility
Disease Outbreaks
Drag Force
Vaccines
Immune system
Vaccine
Immune System
Percent
Drag

Keywords

  • Ebola virus
  • genetically engineered bacteria
  • microfluidic viral attenuator

ASJC Scopus subject areas

  • Biotechnology
  • Genetics
  • Applied Mathematics

Cite this

Computational Models for Trapping Ebola Virus Using Engineered Bacteria. / Martins, Daniel Perez; Barros, Michael; Pierobon, Massimiliano; Kandhavelu, Meenakshisundaram; Lio, Pietro; Balasubramaniam, Sasitharan.

In: IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol. 15, No. 6, 8359015, 01.11.2018, p. 2017-2027.

Research output: Contribution to journalArticle

Martins, Daniel Perez ; Barros, Michael ; Pierobon, Massimiliano ; Kandhavelu, Meenakshisundaram ; Lio, Pietro ; Balasubramaniam, Sasitharan. / Computational Models for Trapping Ebola Virus Using Engineered Bacteria. In: IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2018 ; Vol. 15, No. 6. pp. 2017-2027.
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